Non-random patterns of spider species composition in an Atlantic rainforest

2008·4 MB·English

by  Clarissa Machado Pinto-Leite

2008. The Journal ofArachnology 36:448-452
Non-random patterns of spider species composition in an Atlantic rainforest
Clarissa Machado Pinto-Leite, Agustin Camacho Guerrero, and Tania Kohler Brazil; Departamento deZoologia, Institute
de Biologia, Universidade Federal da Bahia, Rua Barao de Geremoabo, Campus Universitario de Ondina, 40170-210,
Salvador, BA, Brazil. E-mail: [email protected]
Abstract. Spiderspecies respond differentlytovariationsin habitatstructure; thus,differencesin habitat structuremaybe
responsible forvariationsin speciescomposition ofassemblages. However, littleinformationexistson patternsofvariation
in spider species composition in tropical rainforests. We collected spiders and measured five different microhabitat
characteristics in 20 sampling plots distributed among secondary and primary forest patches in an Atlantic rainforest,
Brazil. Using multivariate analysis (non-metric multidimensional scaling - NMS), we checked for the existence of non-
random patterns in the species composition ofaerial (AG) and ground (GG) macroguilds, respectively. We also explored
the relationshipsofthosepatternswithgradientsin microhabitatcharacteristicsand theinfiuenceofforesttype(primaryor
secondaryforest). Wedetected non-random patternsinspiderspeciescomposition unrelated tomicrohabitatcharacteristics
butdifferingbetween primaryandsecondaryforest plotsforbothmacroguilds. Wediscusspossibleimplicationsforstudies
ofspider species composition and spider conservation in tropical forests.
Keywords; Araneae, community ecology, microhabitat gradients, guilds, conservation, tropical forests
Resumo. As especies de aranhas respondem de modo distinto a variances na estrutura do habitat. For esta razao,
difereny'as nestasestruturas poderiam ser responsaveis pela variagao na composigao de especies das assembleias. Contudo,
existe pouca informa(;ao a respeito de padroes na variay'ao da composi(;ao dasassembleiasdearanhas em fioresta tropical.
Neste trabalho, foram coletadas aranhas e mensuradas cinco diferentes caracteristicas de micro-habitat em 20 unidades
amostrais distribuidas em areas de fioresta primaria e secundaria de fioresta tropical Atlantica. Utilizando analises
multivariadas (ordenagao multidimensional nao metrica NMS), procurou-se a existencia de padroes nao aleatorios na
composigaodeespeciesdearanhasdemacroguildasaereas(AG)edechao(GG), respectivamente. Investigou-setambem,a
relagao destes padroes com gradientes nas caracteristicas de micro-habitat e a infiuencia do tipo de fioresta (fioresta
primaria e secundaria). Foram detectados padroes nao aleatorios na composigao deespecies de aranhas, nao relacionados
as caracteristicas de micro-habitat, todavia infiuenciados pelo tipo de fioresta. Discute-se, portanto, a possivel
problematica de estudos que abordam composigao e conservagao de especies de aranhas em fiorestas tropicais.
Theknowledge ofspeciescomposition patternscan be a useful tool & Deeleman-Reinhold 2005; Nogueiraet al. 2006; Barlowetal. 2007;
for habitat management planning directed towards conservation Bragagnolo et al. 2007). Primary forest fragments have usually been
(Primack & Rodrigues 2001). However, with the disturbance of the considered homogeneous in their conditions when compared to
last remnants of the original habitat (Myers et al. 2000) we might secondary fragments (Floreen & Deeleman-Reinhold 2005; Nogueira
loose the chance of rescuing the original patterns of local spider et al. 2006; Barlow et al. 2007; Bragagnolo et al. 2007). However, the
species distribution. best preserved forest remnantsconsists ofa mixture ofsecondaryand
Spiders select different structures for living in their habitats primary forest, supporting the possibility of gradients in structural
(Robinson 1981; Greenstone 1984; Heikkinen & MacMahon 2004) characteristics(as theyfunction asmicrohabitatsforspiders)towhich
and their populations respond to structural gradients in the habitat the spatial species turnover might be related.
(Colebourn 1974; Lubin et al. 1993). Different characteristics of The exuberant diversity ofarthropods in tropical areas requires a
spider assemblages, like abundance of some groups, richness, or considerable effort for collecting, classifying, and analyzing local
diversity, also change along gradients in vegetation density (Rypstra taxocenoses (Lawton et al. 1997). Hofer & Brescovit (2001) divided
1983, 1986; Balfour& Rypstra 1998; Gunnarsson 1988, 1990; Halaj et Neotropical spiders into guilds the members of which forage in the
al. 1998). This is a result ofthe different responses ofspecies exposed same microhabitats. Classifications like this allow us to separate the
to the samegradients (Raizer& Amaral 2001; Wagneret al. 2003). In high levels ofdiversity present in tropical rainforests into ecologically
this way, gradients in vegetation structure might be responsible for recognizable and analytically treatable groups. Therefore, it becomes
gradients in species composition. easier to associate gradients of species composition to gradients of
Most previous studies of tropical forest spider assemblages have microhabitat availability.
compared richness estimators (Alvares et al. 2004; Sorensen 2004; In this study, we looked for non-random patterns of spider
Candiani et al. 2005; Indicatti et al. 2005; Oliveira-Alves et al. 2005; composition in aerial and ground spider guilds in an Atlantic
Dias et al. 2006; Nogueira et al. 2006), diversity and community rainforest fragment in northeastern Brazil, and tested if they were
structure indices between different rainforest fragments (Greenstone related to gradients of microhabitat availability. We also tested if
1984; Russel-Smith & Stork 1994; Floren & Deeleman-Reinhold species composition and microhabitat gradients differ between
2005; Barlow et al. 2007). Studies on assemblage composition in primary and secondary forest fragments. Finally, as spider species
rainforest fragmentshavebeen limitedtosunnyregionsofrainforests, inventories are scarce in this region ofSouth America, we provide a
such as canopies (Russel-Smith & Stork 1995) and clearings (Peres et list ofspecies with abundance data as online material.
al. 2007). Therefore, we know almost nothing about the patterns of METHODS
variation in spider species composition in the shaded regions of
rainforests. Field work took place in the Fazenda Camurujipe (12°30'5"S,
Arachnid assemblages in primary forest fragments exhibit higher 38°2'19"W), a privatefarm, ownedbytheGarcia D’Avila foundation,
spatial species turnover whencompared to secondary forests(Floreen and located in the in Agu daTorrevillage, Mata de SaoJoaodistrict.
448
PINTO-LEITE ET AL.-NON-RANDOM PATTERNS OF SPECIES COMPOSITION 449
s'jcrw ;s'2rorw ss'rcrw than 15 cm incircumference. Wealso measured thediameterat breast
height of all trunks with more than 15 cm in circumference. All
measurements were madewithin a 5 m radius around 4 points placed
m
10 apart.
Analysis. We deleted all singletons from the analysis, since their
position in one plot does not give reliable information on their
ecological requirements. We divided the species into two “macro-
guild” matrices, according to Holer & Brescovit (2001). The first
macroguild matrix (aerial macroguild, AG), included species belong-
ing to guilds that forage at medium height in the understory such as
nocturnal aerial runners (Anyphaenidae. Clubionidae, Mimetidae,
Salticidae, Segestriidae), aerial ambushers Thomisidae), sedentary
sheet weavers (Pholcidae and Pisauridae), aerial space web builders
(Dictynidae and Theridiidae), aerial orb weavers (Araneidae, Tetra-
gnathidae, Uloboridae, and Theridiosomatidae), nocturnal aerial
ambushers (Senoculidae, Sparassidac, and Salticidae), and diurnal
aerial hunters (Oxyopidae). The ground macroguild (GG) included
species belonging to guilds that forage on theground: diurnal ground
runners (subfamilies Castianeirinae and Corinninae from Corinni-
dae), nocturnal ground weavers (Deinopidaeand Dipluridae), diurnal
ground weavers (Mysmenidae and Linyphiidae), ground ambushers
(Idiopidae), and leaf litter stalkers (Miturgidae). The morphospecies
— belonging to Euophryinae (Salticidae), Nothrocteiuis Badcock 1932,
Figure 1. Map of study area, with position of sampling plots Celaetycluieus Simon 1897 and Cteniis Walckenaer 1805 (Ctenidac)
among vegetation types, and location ofstudy site inside the state of should belong to the aerial macroguild according to the classification
Bahia, northeastern Brazil. proposed by Hofer & Brescovit (2001). However, our observations
indicated that theyforage on the leaflitterand thusweincluded them
100 kmnorthtoSalvadordeBahia,northeasternBrazil.Thisfragment in the ground macroguild. A tree fell over plot “h” between the
contains 1,390 ha ofombrophylous lowland rainforest and presents a samplingtrips; thereforewedecidedtoremoveitfrom theordinations
softly undulated geomorphology, typical for the region (Ab’saber but maintained it in the total counts and the species list.
1977). A part of the forest was partially logged 35 years before but To detect non-random variation axes in species composition, we
primaryforest still exists. Thisfragment is oneofthe best preserved in performed a non-metric multidimensional scaling (NMS) analysis on
the northern littoral of Bahia. This makes it critically important for each macroguild matrix using PC-ORD® (see McCune & Grace
conservation and study of the arachnofauna since significant forest (2002) for a comprehensive explanation of NMS method). NMS
patchesarevirtuallynonexistentinNortheastern Brazil(Morellatoand orders the plots on axes according to their similarity in species
Haddad 2000). Mean temperatures in this region vary between 21°C composition. In thisway, therelativesimilarityinspeciescomposition
and 26°C. Annual rainfall reaches 2000 mm, and rains are more among plots is represented by the differences between their axis
concentratedfrom MarchtoJuly(InstitutoNacionaldeMeteorologia. scores. NMSdoesnot assumelinearrelationshipsbetweenspeciesand
Online at http://ww—w.inmet.gov.br). environmental gradients. Because of that it is especially appropriate
Sampling design. We sampled in 20 rectangular plots of30 m X for reduction of species composition matrices, which seldom fulfil
5 m identified by letters (a, b, c, d...o; Fig. 1). Two complementary those assumptions. Our choices for performing the analysis followed
sampling methods were used: beating tray and hand collecting by recommendationsfrom McCune& Grace(2002). First, weperformed
visual searching. We used the beating-tray method to sample 15 an exploratory analysis in the PC-ORD®program (McCune& Grace
bushes (all ^ 3 m in height) of different species per plot, selected 2002) to detect the best options for representation of variation in
haphazardly. In each plot we invested an effort of two persons per species composition. We used the following choices: 6 possible
hour in each expedition ofactive diurnal searches. We sampled each dimensions, instabilitycriterion of0.005, 500iterations, 999runswith
plot once in each of two five-day expeditions (January and March real data and 999 runs with randomized data. As the exploratory
2006). We distributed the plots systematically in the forest fragment. analysis indicated that one axis ordination was recommended, we
To do this, we walked 5 minutes along the main trails and then represented the variation of each macroguild matrix on one axis.
randomly chose the side ofthe trail and the distance from the plot to Abundances ofeach species in each plot were divided by the total of
the trail (10 to 100 m). After a plot was established, we came back to spider caught in each plot. Relative abundances were analyzed, the
themaintrail andrepeated theprocess. Theforest fragmentpresented Bray Curtis coefficient was selected as the distance measure, and we
two forest types (data from the state’s environmental resources used a random starting point and 500 runs with real data to find the
council, Superintendencia de Politicas Florestais, Conservaijao e best representation ofthe data on one axis (McCune & Grace 2002).
Biodiversidade. Online at http://www.meioambiente.ba.gov.br/); thus Weapplied a MonteCarlo test, with 999 runs ofrandomized data, to
weplaced 12 plots in secondary forest (35 years old) and 8 in original test ifour ordination was expected from a randomized version ofthe
primary forest (Fig. 1). Thetaxonomist, A.D. Brescovit, classified the composition matrix. Our criterion for evaluating stability of the
specimens to species or morphospecies level. Specimens were solution was standard deviation in stress equal to or less than 0.002,
deposited in the Butantan Institute’s Collection (IBSP, curator A.D. with 100 iterations to evaluate stability and 500 as the maximum
Brescovit) and the Zoology Museum of the Federal University of numberofiterations. Finally, thecorrelation ofthedistances between
Bahia (MZUFBA, curator T.K. Brazil). plots in the original abundance matrices with the distances in new
—
Measurement of microhabitat availability. In each plot we ordered matrices was evaluated using a Mantel’s test. We calculated
measured the availability of five different microhabitat characteris- the significance of the correlation via Monte Carlo randomization
tics. Leaf litter cover and grass cover were estimated according to method with 999 randomizations.
Fournier’s scale (Fournier 1974). We counted the number of fallen We represented the main gradients in microhabitat descriptors
trunks with more than 15 cm in circumference and saplings with less across all the plots by performing a Principal Component Analysis
—
450 THE JOURNAL OF ARACHNOLOGY
—
Table 1. Descriptive statistics of microhabitats, measured in an Atlantic Rainforest fragment, northeastern Bahia. Abbreviations: DBH,
diameter at breast height; GC, grass cover; LC, leaflitter cover; NS, number ofsaplings; NET, number offallen trunks.
n Range Min. Max. Mean S.D.
Grass cover (%) 19 55.0 25.0 80.0 57.1 16.9
Leaflitter cover (%) 19 15.0 85.0 100.0 96.6 5.3
Number offallen trunks 19 19.8 4.0 23.8 13.1 6.1
Diameter at breast height (cm) 19 457.3 214.5 671.8 439.2 153.3
Number ofsaplings 19 24.8 7.6 32.4 18.0 5.9
(PCA), based on the correlation matrix and using varimax rotation composition gradients detected by the NMS analyses. Visually
(SPSS 12 for windows program). We tested the relationship between assessed normality ofresiduals did not deviate seriously from it.
NMS and PCA axes via linear regression. To test the difference in Comparison ofprimary and secondary forest. Despite the fact that
species composition and microhabitats between primary and second- the two macroguilds showed morevariation in speciescomposition in
ary forest plots, we first performed a Levene test to detect differences the primary forest (Mean ± SD (range); AG; 0.31 ± 1.39 (—2.61 to
in composition variation (beta diversity), and a Welch /-test to detect 2.25); GG; 0.83 ± 0.93 (—0.80 to 2.16) than in the secondary forest
differences in NMS and PCA scores (differences in species (AG; -0.13 ± 0.58 (-0.86 to 1.07); GG; -0.65 ± 0.40 (-1.36 to
composition and microhabitat availability). -0.07), the differences were significant only for the AG NMS axis
(Levene’stest P = 0.018). Welch’s /-testforunequalvariancesshowed
RESULTS
that primary and secondary forest types differed in species
speScaimmpelnisngwerreseulctlsa.s—sifFiredomintaoto2t6alspoefci2e0s82ancdoll1e0c4temdorspphidoesrpse,c6i5e4s.adTuhlet ctoomGpoGsi(t/io=n4(.3N7M7,Sdsfco=re1s0;onsttahnedaarxdisergreonreroafteddi)ffeornelnycewi0t.3h39r;esPpec=t
(fP1ai13ms20ia.lu5sirp%eie)scdiaaewensedwrwieTethrhoeSmaoildntislisiyctdiraodiaenbeuewtieswtdpihetich9nies3s3p2e2(cf1ia3esm%spie)l(c,i9ie.esTs.6h%eT)r(hi2(eds4ie.ief2do%oaunerloimwfnioetsihltinsdt2ai7avbtiusdnhputedatclapsi:n)e/t,s/ 0db1.5fe0,t0=ws1e)t.1ea6nn,dDaspirtrfdaifnemerdarearrnryocdreaseonrfdradoimrsfoefocneforgnednidcfaPefrCey=rAefn0oc.rpe4el6so=7tt;p0Psl.co4to=5sr3e;0(s.PP3C7wI0=e;3r;e0/.P6=Cn52o2t;50)../9s2=iT3gh6n0u,i.sf4id,5cf8aw8n=e,t
www.redezoo.ufba.br/Spccieslist.htm). The most abundant and spe- found no gradients in microhabitat availability between primary and
cies rich guild was the nocturnal aerial runners with 741 specimens secondary forest plots that might explain the differences in species
composition.
and 46 species. Sedentary sheet weavers was the second most
abundant with 359 specimens. The second richest guild was the aerial DISCUSSION
space web builders with 27 species, followed by aerial orb weavers
with 24species. Twoguilds, ground ambushersand leaflitterstalkers, Both aerial and ground macroguilds showed one non-random axis
were represented only by singletons, thus they were deleted from the of variation in species composition. Significant variations in species
composition oftropical spider assemblages have been reported from
analyses.
—NMS comparisons between different fragments, usually related to different
Gradients in species composition. detected a single non- stages of ecological succession (Floren & Deeleman-Reinhold 2005;
random axis of variation for each of the two macroguilds (AG: 62
species, 15 families, Montecarlo P = 0.004, stress: 29.5%, instability: Nogueira et al. 2006) orwhen comparingEucalyptusplantationswith
0.025; GG: 9 species, 4 families, Montecarlo E = 0.15, stress 27.2%, forest fragments in different stages of regeneration (Barlow et al.
instability: 0.015). The Mantel test showed that 66% of the original 2007). Nogueira et al. (2006) suggested that differences in vegetation
differences in species composition from AG and 73% from GG were structure between fragments in different forest stages of succession
explained by the NMS axes. Stress values close to 30% are high. mreilgahtteddettoemrimcirnoehatbheitvaatridaitvieornsiitnysapniddermiscpreocicelsimcaotmepocsointdiiotni,onssi.nceitis
(inHnouMswmctaebCbveuielrnriet,oyfc&sprtlirotGetesrsrsai(ocd6ne2ewps2aep0sne0cd2ais)le,ssooiwnnnhoi2ttc0hmhepeltinostufsmvo)rebiretnyhrtehhoAeifgGchasspaweexhicosief.ensAThGriienslmamtathteeerdainxmts.aottTrthhiahexte aR1sy9p9Ti3shm)teproaaarnvtdaai1l9nga8tub8ii;lfldoisrtGyu(snoRpnfyiadpsersortsmrspeaoonpm1ui9lc81ar39to,8ih8oa,1nb9si8t169a;(9tC0sGo)rl.heeaebsInonsubtreooneunnre1w9is71dt49eu;8ld4yy;L,urBbeahiclonofwgoeneuvtir.ezre&a,dl
titheeraotridoinns.atDiounemtaoythgiisvefadcitf,fewreentperrefsuolrtmseddeptehendoirndginoantitohneonfumthbeerAoGf gvraarsisatcioovneri,n nthuembaveariloabfislaiptlyinogfsd,inffuemrebnetrvoegfedteaatidontrautntkrsibaunteds,disaumcehtears
matrix several times and observed that the ordination of the non- at breast height, did not show any effect on spider species
random gradient in species composition was indeed constant, going composition.
from the plots a, b, c, d, o, to plotsj, k,—1, m. The extremely high spider species richness typical for tropical
Reduction of microhabitat descriptors. PCA generated two axes regions makes it difficult to detect a single variable that influences
(PCs)that representeda reasonablepartofthetotalvariation(74.5%) whole assemblages. However, we grouped the species sampled by
in microhabitat characteristics. The first axis (PCI: 44% of total similarity in microhabitat use (aerial and ground macroguilds) and
variation), represented number ofsaplings (loading: 0.914), and leaf then related the macroguilds to the main gradients in microhabitat
litter cover (loading: 0.871). The second axis (PC2: 30.5% of total availability (PCI and PC2), representing several microhabitat
variation) represented increasing diameter breast height of trees descriptors at the same time. Theoretically, this should increase our
(loading: 0.758) and grass cover (loading: 0.689), and decreasing ability to find an influence on species composition. As shown in
number of fallen trunks (loading: -0.729). A description of Table 1, the ranges of variation in microhabitat availability were
environmental variables is presented in Table 1. variable among the different descriptors. However, they might not
The multiple regression analysis showed that none ofthe two PCs havebeenenough toinfluencetherelativeabundanceofanimportant
weresignificantly relatedtothespeciescomposition axes(AG: PCI: b numberofspiderspecies. Russel-Smith & Stork (1995) studied spider
= 12016.14; P = 0.59; PC2; b = 4616.160; P = 0.83; GG; PCI; b = species composition along the canopy of a humid tropical forest in
9529.61; P = 0.72, PC2; b = 7086.47; P = 0.84). This indicates that Borneo and did not find any influence of tree structural and
the microhabitat characteristics measured did not affect the species taxonomicvariation on speciescomposition. Pereset al. (2007) found
PINTO-LEITE ET AL.-NON-RANDOM PATTERNS OF SPECIES COMPOSITION 451
differences in composition ofspiderassemblages in an Atlantic forest recolonization in adjacent patches of habitat, even with the highest
Ij
fragment when comparing natural treefall gaps with the surrounding investments and the best techniques in vegetation restoration, most
, forest. Additionally, they found significant differences in habitat spiderspeciesmightbedoomedtoextinctionintropicalforests. Density
1
structure and microclimate conditions. These results suggest that dependence tests in recolonization ability ofspider species, controlling
j gradients of spider species composition in tropical forests might be for microhabitat dependence, could shed light on this problem.
f
related to strong variations in microclimate conditions, such as those ACKNOWLEDGMENTS
i' related to treefall gaps, instead of variation in the availability of
different physical structures or microhabitats. However, additional We would like to thank Juliana Costa Piovesan, Myna Lizzie,
j
experimental studies on rainforest spiders’ tolerance to perturbation Mariana Vila-Flor, Dary Rigueira, Lina Almeida, Milena Camar-
?
in microhabitat availability should illuminate their sensibility to delli, Joao Anderson de Goes, and Claudio Jose da Silva for helping
human made perturbations. during field work. Adriano Paiva, the biologist responsible for
Another reason for not finding significant relationships between management ofGarcia D’Avila foundation’s lands, for allowing this
microhabitatavailabilityand non-randomchangesin thecomposition study there; Mariana Cayres, from the Regional Environmental
of spider assemblages are that other, stronger, factors are affecting Council, for creating the vegetation map; Dr. Antonio Brescovit, for
them. In our study, both axes of species composition were spider identification; Silvanir Souza and Jaqueline Souza for help to
significantly affected by the stage of ecological succession of the provide a list of species as online material; Cristina Rheims and
i patch: AG presented higher variation in species composition among Thiago de Sa for help with the translation. This study was supported
I plots from the primary forests, and species composition was by grants (scientific initiation) from FAPESB 3367/2005.
I significantly different for GG. Since only one patch ofeach stage of
1
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